Narayanavadivoo Gopinathan Bhuvaneswari Amma

Orcid: 0000-0003-3660-380X

Affiliations:
  • National Institute of Technology, Tiruchirappalli, India


According to our database1, Narayanavadivoo Gopinathan Bhuvaneswari Amma authored at least 13 papers between 2018 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of five.

Timeline

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Bibliography

2024
CLNet: a contactless fingerprint spoof detection using deep neural networks with a transfer learning approach.
Multim. Tools Appl., March, 2024

Towards improving the performance of traffic sign recognition using support vector machine based deep learning model.
Multim. Tools Appl., January, 2024

2023
Detection of DoS Attacks in Smart City Networks With Feature Distance Maps: A Statistical Approach.
IEEE Internet Things J., 2023

2022
Optimization of vector convolutional deep neural network using binary real cumulative incarnation for detection of distributed denial of service attacks.
Neural Comput. Appl., 2022

LPCOCN: A Layered Paddy Crop Optimization-Based Capsule Network Approach for Anomaly Detection at IoT Edge.
Inf., 2022

A vector convolutional deep autonomous learning classifier for detection of cyber attacks.
Clust. Comput., 2022

IoTInDet: Detecting Internet of Things Intrusions with Class Scatter Ratio and Hellinger Distance Statistics.
Proceedings of the Information Systems Security - 18th International Conference, 2022

2021
A statistical class center based triangle area vector method for detection of denial of service attacks.
Clust. Comput., 2021

2020
A Statistical Approach for Detection of Denial of Service Attacks in Computer Networks.
IEEE Trans. Netw. Serv. Manag., 2020

Anomaly detection framework for Internet of things traffic using vector convolutional deep learning approach in fog environment.
Future Gener. Comput. Syst., 2020

SAGRU: A Stacked Autoencoder-Based Gated Recurrent Unit Approach to Intrusion Detection.
Proceedings of the Intelligent Data Engineering and Analytics, 2020

2019
Deep Radial Intelligence with Cumulative Incarnation approach for detecting Denial of Service attacks.
Neurocomputing, 2019

2018
VCDeepFL: Vector Convolutional Deep Feature Learning Approach for Identification of Known and Unknown Denial of Service Attacks.
Proceedings of the TENCON 2018, 2018


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